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The best solution to assign opportunities based on zip code and sales area is to configure territory management feature to support opportunity assignment. Territory management is a feature that allows you to organize your sales team into territories based on criteria such as geography, industry, product line, or customer segment. You can assign accounts and opportunities to territories using assignment rules or manual sharing. You can also define forecast managers and roll up forecasts by territory45. Assign opportunities using list views using zip code is not a good solution because it is inefficient and does not support reporting by sales area. Add custom fields in opportunities for zip code and use assignment rules is not a good solution because it requires creating additional fields and does not support reporting by sales area. Allow sales users to manually assign opportunity ownership based on zip code is not a good solution because it is prone to errors and does not support reporting by sales area.

Grouping batches by the AccountId field can improve the performance and avoid locking issues when loading Opportunity records using the Bulk API in parallel mode1. This is because the AccountId field is indexed and can be used to distribute the records evenly across batches

To improve the dashboard performance, the data architect should use selective queries to reduce the amount of data being returned, de-normalize the data by reducing the number of joins, and reduce the amount of data queried by archiving unused opportunity records. These options will help optimize the query performance, reduce the query complexity, and free up storage space. Option C is incorrect because removing widgets from the dashboard to reduce the number of graphics loaded will not affect the dashboard performance significantly, and may reduce the usability and functionality of the dashboard. Option D is incorrect because running the dashboard for CEO and sending it via email will not improve the dashboard performance, but rather shift the burden to another user.

According to the official Salesforce guide1, assigning leads to a single dummy user can cause performance issues and data skew, especially if the dummy user owns more than 10,000 records. Data skew occurs when a single user or a small number of users own a disproportionately large number of records, which can affect query performance and sharing calculations. Option B is the correct answer because it suggests creating multiple dummy users and assigning leads to them, which can distribute the load and reduce data skew. Option A is incorrect because assigning the dummy user to the last role in the role hierarchy does not affect the performance or data skew issues. Option C is incorrect because assigning the dummy user to the highest role in the role hierarchy can worsen the performance and data skew issues, as it will grant access to more users and records. Option D is incorrect because periodically deleting leads can cause data loss and does not address the root cause of the problem.

The three key steps that a data architect should take when merging data from multiple systems into Salesforce are:

• Analyze each system’s data model and perform gap analysis. This step involves understanding the structure and meaning of the data in each system, identifying the common and unique data elements, and mapping the data fields between the systems. This step also involves assessing the quality and consistency of the data, and identifying any data cleansing or transformation needs.
• Utilize an ETL tool to merge, transform, and de-duplicate data. This step involves using an ETL tool to connect to the source systems, extract the data, apply any data transformations or validations, and load the data into Salesforce. This step also involves applying de-duplication rules or algorithms to avoid creating duplicate records in Salesforce.
• Work with stakeholders to define record and field survivorship rules. This step involves collaborating with the business users and owners of the data to determine which records and fields should be retained or overwritten in case of conflicts or discrepancies. This step also involves defining the criteria and logic for record and field survivorship, and implementing them in the ETL tool or in Salesforce.

Creating new fields to store additional values from all the systems is not a key step, but rather a possible outcome of the gap analysis. It may not be necessary or desirable to create new fields for every value from every system, as it may result in redundant or irrelevant data. Installing a 3rd party AppExchange tool to handle the merger is not a key step, but rather a possible option for choosing an ETL tool. It may not be the best option depending on the requirements, budget, and preferences of the organization.